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    COVID-19 biomarkers and their overlap with comorbidities in a disease biomarker data model

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    Author
    Gogate, Nikhita
    Lyman, Daniel
    Bell, Amanda
    Cauley, Edmund
    Crandall, Keith A.
    Joseph, Ashia
    Kahsay, Robel
    Natale, Darren A.
    Schriml, Lynn M.
    Sen, Sabyasach
    Mazumder, Raja
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    Date
    2021-11-05
    Journal
    Briefings in Bioinformatics
    Publisher
    Oxford University Press
    Type
    Article
    
    Metadata
    Show full item record
    See at
    https://doi.org/10.1093/bib/bbab191
    http://www.ncbi.nlm.nih.gov/pmc/articles/pmc8195003/
    Abstract
    Abstract In response to the COVID-19 outbreak, scientists and medical researchers are capturing a wide range of host responses, symptoms and lingering postrecovery problems within the human population. These variable clinical manifestations suggest differences in influential factors, such as innate and adaptive host immunity, existing or underlying health conditions, comorbidities, genetics and other factors-compounding the complexity of COVID-19 pathobiology and potential biomarkers associated with the disease, as they become available. The heterogeneous data pose challenges for efficient extrapolation of information into clinical applications. We have curated 145 COVID-19 biomarkers by developing a novel cross-cutting disease biomarker data model that allows integration and evaluation of biomarkers in patients with comorbidities. Most biomarkers are related to the immune (SAA, TNF-∝ and IP-10) or coagulation (D-dimer, antithrombin and VWF) cascades, suggesting complex vascular pathobiology of the disease. Furthermore, we observe commonality with established cancer biomarkers (ACE2, IL-6, IL-4 and IL-2) as well as biomarkers for metabolic syndrome and diabetes (CRP, NLR and LDL). We explore these trends as we put forth a COVID-19 biomarker resource (https://data.oncomx.org/covid19) that will help researchers and diagnosticians alike. © The Author(s) 2021.
    Sponsors
    National Science Foundation
    Keyword
    cancer
    COVID-19
    COVID-19 biomarkers
    metabolic syndrome
    vascular disease
    Identifier to cite or link to this item
    http://hdl.handle.net/10713/17641
    ae974a485f413a2113503eed53cd6c53
    10.1093/bib/bbab191
    Scopus Count
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    UMB Coronavirus Publications
    UMB Open Access Articles

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